Data in tabular format is frequently occurring in real-world applications. Graph Neural
Networks (GNNs) have recently been extended to effectively handle such data, allowing …

Conformal inference or prediction is a method in statistics to yield resilient uncertainty
bounds for predictions from black-box models regardless of any presupposed data …

Artificial Intelligence (AI) methods are an integral part of modern decision support systems.
The best-performing predictive models used in AI-based decision support systems lack …

Many machine learning algorithms for tabular data produce black-box models, which
prevent users from understanding the rationale behind the model predictions. In their …

This thesis presents the development and refinement of the UVEMAP system, an Uncertainty-
aware Vision-based Ego-Motion-Aware target Prediction module designed for robust multi …

Recently, machine learning algorithms have achieved state-of-the-art performance in real-
life applications in various domains, but such algorithms tend to produce non-interpretable …